Learn about the technique that encourages AI to reason step-by-step, improving accuracy on complex logic and math problems.To learn more, visit https://www.domainshift.ai/p/chain-of-thought-prompting
Discover how models perform tasks they’ve never seen during training, using only instructions and general knowledge.To learn more, visit https://www.domainshift.ai/p/zero-shot-learning
Explore how models can learn new tasks with only a few examples, demonstrating remarkable adaptability and transfer learning capabilities.To learn more, visit https://www.domainshift.ai/p/few-shot-learning
Understand the phenomenon where AI models generate false or nonsensical information that appears plausible and convincing.To learn more, visit https://www.domainshift.ai/p/hallucination
Learn how external information retrieval systems enhance language models, reducing hallucinations and improving factual accuracy.To learn more, visit https://www.domainshift.ai/p/retrieval-augmented-generation
Discover how pre-trained models are adapted for specific tasks by training further on smaller, task-specific datasets.To learn more, visit https://www.domainshift.ai/p/fine-tuning
Explore the craft of designing and optimizing inputs to guide AI models toward generating desired, accurate outputs.To learn more, visit https://www.domainshift.ai/p/prompt-engineering
Understand how words and concepts are converted into numerical vectors that capture semantic meaning and relationships in vector space.To learn more, visit https://www.domainshift.ai/p/embeddings
Learn about the basic units into which text is divided for processing, the foundation of how language models understand text.To learn more, visit https://www.domainshift.ai/p/tokens
Discover massive AI models trained on vast text data that can understand and generate human-like text across diverse applications.To learn more, visit https://www.domainshift.ai/p/large-language-models
Explore the AI field dedicated to helping computers process, interpret, and generate human language as it's spoken and written.To learn more, visit https://www.domainshift.ai/p/natural-language-processing
Understand how AI quantifies the difference between predicted and actual outputs to measure and optimize model performance. To learn more, visit https://www.domainshift.ai/p/loss-function
Learn about the fundamental optimization algorithm that trains machine learning models by iteratively adjusting parameters to minimize loss. To learn more, visit https://www.domainshift.ai/p/gradient-descent
Explore how multiple attention operations run in parallel, each capturing different types of relationships within the data. To learn more, visit https://www.domainshift.ai/p/multi-head-attention
Discover how sequences attend to themselves, allowing each position to consider all other positions when computing representations.To learn more, visit https://www.domainshift.ai/p/self-attention
Understand how models learn to focus on relevant parts of input by assigning weights, dramatically improving sequence processing tasks.To learn more, visit https://www.domainshift.ai/p/attention-mechanism
Learn about the revolutionary architecture that uses attention mechanisms to process entire sequences simultaneously, powering today’s most advanced language models.To learn more, visit https://www.domainshift.ai/p/transformer-architecture
Explore the advanced RNN architecture that solves the vanishing gradient problem, enabling networks to remember information across longer sequences. To learn more, visit https://www.domainshift.ai/p/long-short-term-memory
Discover neural networks with memory that process sequential data by maintaining information about previous inputs, perfect for time series and language tasks.To learn more, visit https://www.domainshift.ai/p/recurrent-neural-networks
Learn about specialized neural networks designed for visual data that revolutionized computer vision by automatically learning to detect image features. To learn more, visit https://www.domainshift.ai/p/convolutional-neural-networks